| Multi-fidelity approach to predicting multi-rotor aerodynamic interactions O Pinti, AA Oberai, R Healy, RJ Niemiec, F Gandhi AIAA Journal 60 (6), 3894-3908, 2022 | 16 | 2022 |
| Deep learning and computational physics (lecture notes) D Ray, O Pinti, AA Oberai arXiv preprint arXiv:2301.00942, 2023 | 7 | 2023 |
| A multi-fidelity approach to predicting rotor aerodynamic interactions O Pinti, R Niemiec, AA Oberai, F Gandhi Aiaa Aviation 2020 Forum, 2796, 2020 | 6 | 2020 |
| Graph Laplacian-based spectral multi-fidelity modeling O Pinti, AA Oberai Scientific Reports 13 (1), 16618, 2023 | 2 | 2023 |
| Multi-Fidelity Surrogate Model for Interactional Aerodynamics of a Multicopter OPA Oberai, RHRNF Gandhi | 2 | 2021 |
| Aeroacoustic Reduced-Order Models Based on a priori/posteriori Data Analysis R Arina, O Pinti 25th AIAA/CEAS Aeroacoustics Conference, 2680, 2019 | 1 | 2019 |
| Operator Networks D Ray, O Pinti, AA Oberai Deep Learning and Computational Physics, 87-119, 2024 | | 2024 |
| Residual Neural Networks D Ray, O Pinti, AA Oberai Deep Learning and Computational Physics, 41-48, 2024 | | 2024 |
| Introduction to Deep Neural Networks D Ray, O Pinti, AA Oberai Deep Learning and Computational Physics, 9-39, 2024 | | 2024 |
| Solving PDEs with Neural Networks D Ray, O Pinti, AA Oberai Deep Learning and Computational Physics, 71-86, 2024 | | 2024 |
| Generative Deep Learning D Ray, O Pinti, AA Oberai Deep Learning and Computational Physics, 121-146, 2024 | | 2024 |
| A few-shot graph Laplacian-based approach for improving the accuracy of low-fidelity data O Pinti, AA Oberai arXiv preprint arXiv:2304.04862, 2023 | | 2023 |
| Deep Learning and Computational Physics D Ray, O Pinti, AA Oberai Springer Nature, 0 | | |
Assad OberaiAME, USCVerified email at usc.edu
